Quantum gas microscopes probe quantum many-body lattice states via projective measurements in the occupation basis, enabling access to various density and spin correlations. Phase information, however, cannot be directly obtained in these setups. Recent experiments went beyond this by measuring local current operators and local phase fluctuations. Here we propose how Fourier-space manipulation in a matter-wave microscope allows access to various long-range off-diagonal correlators in experimentally realistic settings, realizing a many-body phase microscope. We demonstrate in particular how the fermionic d-wave superconducting order parameter in arbitrary Hubbard-type models, the non-equal time Green's function yielding the spectral function, or the hidden order of composite bosons in a fractional Chern insulator can be directly measured. Our results show the great potential of matter-wave microscopy for accessing exotic correlators including phases and coherences and characterizing intriguing quantum many-body states.

The spreading of a thin viscous fluid film on a horizontal surface is an interesting problem in fluid mechanics with many practical applications ranging from coating processes to biological systems and environmental flows. It can even be observed in everyday situations, such as syrup spreading on a pancake. We present a project-based learning approach to this problem, in which engineering or physics undergraduates apply classroom knowledge to understand and solve it, using dimensional analysis, experiments, and theoretical modeling. First, a dimensional analysis is conducted to guide the design of the experiment suitable for an undergraduate laboratory or even at home. The problem is then simplified to obtain a mathematical model that accounts for the experimental results. Through this process, students are able to obtain a solution compatible with those published in fluid mechanics journals with minimal supervision from the instructor. This project not only develops important skills but also motivates students by showing that they have the ability to solve complex problems.

Blue-collar work is often highly collaborative, embodied, and situated in shared physical environments, yet most research on collaborative AI has focused on white-collar work. This position paper explores how the embodied nature of AI agents can support team collaboration and communication in co-located blue-collar workplaces. From the context of our newly started CAI-BLUE research project, we present two speculative scenarios from industrial and maintenance contexts that illustrate how embodied AI agents can support shared situational awareness and facilitate inclusive communication across experience levels. We outline open questions related to embodied AI agent design around worker inclusion, agency, transformation of blue-collar collaboration practices over time, and forms of acceptable AI embodiments. We argue that embodiment is not just an aesthetic choice but should become a socio-material design strategy of AI systems in blue-collar workplaces.

The primary aim of Hilbert's proof theory was to establish the consistency of classical mathematics using finitary means only. Hilbert's strategy for doing this was to eliminate the infinite (in the form of unbounded quantifiers) from formalized proofs using the so-called epsilon substitution method. The result is a formal proof which does not mention or appeal to infinite objects or "concept-formations." However, as later developments showed, the consistency proof itself lets the infinite back into proof theory, through a back door, so to speak. The paper outlines the epsilon substitution method as an example of how proof-theoretic constructions "eliminate the infinite" from formal proofs, and how they aim to establish conservativity and consistency. The proof also requires an argument that this proof theoretic construction always works. This second argument, however, requires possibly infinitary reasoning at the meta-level, using induction on ordinal notations.

Temporal graphs represent networks in which connections change over time, with edges available only at specific moments. Motivated by applications in logistics, multi-agent information spreading, and wireless networks, we introduce the D-Temporal Multi-Broadcast (D-TMB) problem, which asks for scheduling the availability of edges so that a predetermined subset of sources reach all other vertices while optimizing the worst-case temporal distance D from any source. We show that D-TMB generalizes ReachFast (arXiv:2112.08797). We then characterize the computational complexity and approximability of D-TMB under six definitions of temporal distance D, namely Earliest-Arrival (EA), Latest-Departure (LD), Fastest-Time (FT), Shortest-Traveling (ST), Minimum-Hop (MH), and Minimum-Waiting (MW). For a single source, we show that D-TMB can be solved in polynomial time for EA and LD, while for the other temporal distances it is NP-hard and hard to approximate within a factor that depends on the adopted distance function. We give approximation algorithms for FT and MW. For multiple sources, if feasibility is not assumed a priori, the problem is inapproximable within any factor unless P = NP, even with just two sources. We complement this negative result by identifying structural conditions that guarantee tractability for EA and LD for any number of sources.

The Schrödinger equation in high dimensions describes the evolution of a quantum system. Assume that we are given the evolution map sending each initial state $f\in L^2(\mathbb{R}^n)$ of the system to the corresponding final state at a fixed time $T$. The main question we address in this paper is whether this initial-to-final-state map uniquely determines the Hamiltonian $-Δ+V$ that generates the evolution. We restrict attention to time-independent potentials $V$ and show that uniqueness holds provided $V \in L^1(\mathbb{R}^n)\cap L^q(\mathbb{R}^n)$, with $q>1$ if $n=2$ or $q\geq n/2$ if $n\geq 3$. This should be compared with the results of Caro and Ruiz, who proved that in the time-dependent case, uniqueness holds under the stronger assumption that the potential exhibits super-exponential decay at infinity, for both bounded and unbounded potentials. This paper extends earlier work of the same authors, where uniqueness was obtained for bounded time-independent potentials with polynomial decay at infinity. Here we only require $L^1$-type decay at infinity and allow for $L^q$-type singularities. We reach this improvement by providing a refinement of the Kenig-Ruiz-Sogge resolvent estimate, which replaces the classical Agmon-Hörmander estimates used previously. Crucially, the time-independent setting allows us to avoid the use of complex geometrical optics solutions and thereby dispense with strong decay assumptions at infinity.

We study low T-phase-rank approximation of sectorial third-order tensors $\mathscr{A}\in\mathbb{C}^{n\times n\times p}$ under the tensor T-product. We introduce canonical T-phases and T-phase rank, and formulate the approximation task as minimizing a symmetric gauge of the canonical phase vector under a T-phase-rank constraint. Our main tool is a tensor phase-majorization inequality for the geometric mean, obtained by lifting the matrix inequality through the block-circulant representation. In the positive-imaginary regime, this yields an exact optimal-value formula and an explicit optimal half-phase truncation family. We further establish tensor counterparts of classical matrix phase inequalities and derive a tensor small phase theorem for MIMO linear time-invariant systems.

This study presents a tree-level calculation of the scattering amplitude for the $lp\to lpγ$ (with a hard photon) process within the framework of Chiral Perturbation Theory. Our calculations, based on the $O(p^2)$ and $O(p^3)$ nucleon-pion Lagrangians, aim to provide a theoretical prediction for the differential cross-section. The result shows that explicit inclusion of the nonzero lepton mass significantly influences the low energy differential cross section for $μp\to μp γ$ process. The kinematic region of the present experimental data is beyond the validity domain of the $χ$PT and is therefore not suitable for determining the low-energy constants (LECs). By comparing our results with future experimental data, we expect to determine the values of the LECs as a further test of $χ$PT as an effective low-energy theory of QCD. The process is of significant interest as it can help to determine the generalized polarizabilities of the nucleon.

We study a multi-agent contracting problem where agents exert costly effort to achieve individually observable binary outcomes. While the principal can theoretically extract the full social welfare using a discriminatory contract that tailors payments to individual costs, such contracts may be perceived as unfair. In this work, we introduce and analyze anonymous contracts, where payments depend solely on the total number of successes, ensuring identical treatment of agents. We first establish that every anonymous contract admits a pure Nash equilibrium. However, because general anonymous contracts can suffer from multiple equilibria with unbounded gaps in principal utility, we identify uniform anonymous contracts as a desirable subclass. We prove that uniform anonymous contracts guarantee a unique equilibrium, thereby providing robust performance guarantees. In terms of efficiency, we prove that under limited liability, anonymous contracts cannot generally approximate the social welfare better than a factor logarithmic in the spread of agent success probabilities. We show that uniform contracts are sufficient to match this theoretical limit. Finally, we demonstrate that removing limited liability significantly boosts performance: anonymous contracts generally achieve an $O(\log n)$ approximation to the social welfare and, surprisingly, can extract the full welfare whenever agents' success probabilities are distinct. This reveals a structural reversal: widely spread probabilities are the hardest case under limited liability, whereas identical probabilities become the hardest case when limited liability is removed.

We show that the iterative Faddeev-Jackiw (FJ) reduction for singular Lagrangian systems constitutes a geometrically constrained instance of the Matrix Bordering Technique (MBT). For a first-order Lagrangian with singular pre-symplectic form, each iteration of the Barcelos-Neto-Wotzasek algorithm produces an extended symplectic matrix of canonical bordered form, \begin{eqnarray} f^{(m)} = \left( \begin{matrix} f^{(0)} & B \\ -B^{\mathsf{T}} & 0 \end{matrix} \right) \end{eqnarray} where the bordering block $B$ is determined by the gradients of the consistency constraints. We prove that the nondegeneracy of the extended matrix is governed by the corresponding Schur complement, which is algebraically isomorphic to the Poisson bracket matrix of constraints. As a consequence, the Faddeev-Jackiw algorithm terminates if and only if the constraint algebra is nondegenerate, i.e., when the constraints form a second-class system. This algebraic characterization provides a rigorous foundation for automating the Faddeev-Jackiw procedure symbolically. We present a fully symbolic implementation in the Wolfram Language, and validate the approach on representative mechanical systems with nontrivial constraint structure. The resulting rule-based engine preserves parametric dependencies throughout the reduction, enabling reliable analysis of degeneracy, structural stability (when no bifurcations occur), and possible bifurcation scenarios as critical parameters are varied.

In two-photon polymerization (TPP), the degree of conversion (DC) of the resin has an effect on a broad range of material properties like refractive index (RI) or stiffness. Heterogeneous DC can substitute material doping and multimaterial structures, and outright enable structure designs not possible otherwise. However, obtaining variable DC in the polymer, typically achieved by implementing a variable exposure dose, is held back due to the lack of software support for fabrication and measurement techniques for validation, adding up to a high barrier of entry. This work presents two major breakthroughs in (3+1)D TPP: design freedom and variable-DC fabrication, that are provided by an open-source slicer, as well as calibration methodology for determination of the RI for any DC. Application examples include grayscale lithography, control over writing direction and trajectories, as well as bio-mimicking microphantoms with carefully engineered 3D RI. Results of the RI calibration demonstrate excellent repeatability, accuracy and stability of variable-DC structures. Supported by in-depth metrological analysis, the goal is to popularize variable DC printing within TPP community and to get more out of the existing TPP systems and workflows. In summary, this work provides a complete toolbox for 3D RI engineering and sets the stage for new inventions enabled by point-wise dose control.

The WFC3\IR channel has an innate non-linear response to incident photons, which is corrected for in the calwf3 pipeline with the NLINFILE reference file. The 2009 solution is based on an average polynomial correction for each IR quadrant and is found to be poorly constrained at high fluence levels (e-) approaching the saturation limit. Using a variety of image types, sources, and sample sequences, we test a new pixel-based linearity correction developed by Shenoy et al. (2025). In nearly all cases, the new correction improves the linearity at fluence levels higher than 50,000 e-, with improvements up to 7% for pixels with fluences approaching the saturation limit (80,000 e-) in the last ima reads. The pixel-based solution also significantly decreases the number of cosmic rays erroneously flagged (due to non-linearity correction errors) during ramp fitting in calwf3, leading to improved photometric accuracy in the calibrated flt data and higher signal-to-noise ratios, particularly in Quad 1 (upper-left detector quadrant). Because the new solution tends to make sources brighter, we recalibrate the five HST flux standards used to compute the IR zeropoints and find a negligible impact (0.1-0.2%) on the published values by Calamida et al. (2024), smaller than the RMS dispersion (0.5%) in the observed to synthetic flux ratios for all five flux standards. The new NLINFILE 9au15283i lin.fits was delivered to CRDS in October 2025 and will be used to reprocess all WFC3/IR imaging and grism observations in the MAST archive. An updated reference file a2412448i lin.fits was delivered in February 2026, improving the results at the highest fluence levels by a few tenths of a percent. Please consult the Addendum for details.

With the proliferation of intelligent healthcare systems, patients' Personal Health Records (PHR) generated by the Internet of Medical Things (IoMT) in real-time play a vital role in disease diagnosis. The integration of emerging blockchain technologies signiffcantly enhanced the data security inside intelligent medical systems. However, data sharing across different systems based on varied blockchain architectures is still constrained by the unsolved performance and security challenges. This paper constructs a cross-chain data sharing scheme, termed MedExChain, which aims to securely share PHR across heterogeneous blockchain systems. The MedExChain scheme ensures that PHR can be shared across chains even under the performance limitations of IoMT devices. Additionally, the scheme incorporates Cryptographic Reverse Firewall (CRF) and a blockchain audit mechanism to defend against both internal and external security threats. The robustness of our scheme is validated through BAN logic, Scyther tool, Chosen Plaintext Attack (CPA) and Algorithm Substitution Attack (ASA) security analysis veriffcation. Extensive evaluations demonstrate that MedExChain signiffcantly minimizes computation and communication overhead, making it suitable for IoMT devices and fostering the efffcient circulation of PHR across diverse blockchain systems.

Liquidation of collateral are the primary safeguard for solvency of lending protocols in decentralized finance. However, the mechanics of liquidations expose these protocols to predatory price manipulations and other forms of Maximal Extractable Value (MEV). In this paper, we characterize the optimal liquidation strategy, via a dynamic program, from the perspective of a profit-maximizing liquidator when the spot oracle is given by a Constant Product Market Maker (CPMM). We explicitly model Oracle Extractable Value (OEV) where liquidators manipulate the CPMM with sandwich attacks to trigger profitable liquidation events. We derive closed-form liquidation bounds and prove that CPMM transaction fees act as a critical security parameter. Crucially, we demonstrate that fees do not merely reduce attacker profits, but can make such manipulations unprofitable for an attacker. Our findings suggest that CPMM transaction fees serve a dual purpose: compensating liquidity providers and endogenously hardening CPMM oracles against manipulation without the latency of time-weighted averages or medianization.

In the framework of diffieties, introduced by Vinogradov, we introduce integrable infinitesimal symmetries and show that they define a one parameter pseudogroup of local diffiety morphisms. We prove some preliminary results allowing to reduce the computation of integrable infinitesimal symmetries of a given order to solving a system of partial differential equations.We provide examples for which we can reduce to a linear system that can be solved by hand computation, and investigate some consequences for the local classification of diffiety, with a special interest for testing if a diffiety is flat.

The COVID-19 pandemic highlighted the limitations of existing epidemic simulation tools. These tools provide information that guides non-pharmaceutical interventions (NPIs), yet many struggle to capture complex dynamics while remaining computationally practical and interpretable. We introduce DEpiABS, a scalable, differentiable agent-based model (DABM) that balances mechanistic detail, computational efficiency and interpretability. DEpiABS captures individual-level heterogeneity in health status, behaviour, and resource constraints, while also modelling epidemic processes like viral mutation and reinfection dynamics. The model is fully differentiable, enabling fast simulation and gradient-based parameter calibration. Building on this foundation, we introduce a z-score-based scaling method that maps small-scale simulations to any real-world population sizes with negligible loss in output granularity, reducing the computational burden when modelling large populations. We validate DEpiABS through sensitivity analysis and calibration to COVID-19 and flu data from ten regions of varying scales. Compared to the baseline, DEpiABS is more detailed, fully interpretable, and has reduced the average normal deviation in forecasting from 0.97 to 0.92 on COVID-19 mortality data and from 0.41 to 0.32 on influenza-like-illness data. Critically, these improvements are achieved without relying on auxiliary data, making DEpiABS a reliable, generalisable, and data-efficient framework for future epidemic response modelling.

Violent cosmic events, from black hole mergers to stellar collapses, often leave behind highly excited black hole remnants that inevitably relax to equilibrium. The prevailing view, developed over decades, holds that this relaxation is rapidly filtered into a linear regime, establishing linear perturbation theory as the bedrock of black hole spectroscopy and a key pillar of gravitational-wave physics. Here we unveil a distinct nonlinear regime that transcends the traditional paradigm: before the familiar linear ringdown, an intrinsically nonlinear, long-lived bottleneck can dominate the evolution. This stage is controlled by a saddle-node ghost in phase space, which traps the remnant and delays the onset of linearity by a timescale obeying a universal power-law. The ghost imprints a distinctive quiescence-burst signature on the emitted radiation: a prolonged silence followed by a violent burst and a delayed ringdown. Rooted in the bifurcation topology, it extends naturally to neutron and boson stars, echoing a topological universality shared with diverse nonlinear systems in nature. Our results expose a missing nonlinear chapter in gravitational dynamics and identify ghost-induced quiescence-burst patterns as clear targets for future observations.

Large MIMO systems rely on efficient downlink precoding to enhance data rates and improve connectivity through spatial multiplexing. However, currently employed linear precoding techniques, such as MMSE, significantly limit the achievable spectral efficiency. To meet practical error-rate targets, existing linear methods require an excessively high number of access point antennas relative to the number of supported users, leading to disproportionate increases in power consumption.Efficient non-linear processing frameworks for uplink MIMO transmissions, such as NL-COMM, have been proposed. However, downlink non-linear precoding methods, such as Vector Perturbation (VP), remain impractical for real-world deployment due to their exponentially increasing computational complexity with the number of supported streams. This work presents ViPer NL-COMM, the first practical algorithmic and implementation framework for VP-based precoding. ViPer NL-COMM extends the core principles of NL-COMM to the precoding problem, enabling scalable parallelization and real-time computational performance while maintaining the substantial spectral-efficiency benefits of VP precoding. ViPer NL-COMM consists of a novel mathematical framework and an FPGA prototype capable of supporting large MIMO configurations (up to 16x16), high-order modulation (256-QAM), and wide bandwidths (100 MHz) within practical power and resource budgets. System-level evaluations demonstrate that ViPer NL-COMM achieves target error rates using only half the number of transmit antennas required by linear precoding, yielding net power savings on the order of hundreds of Watts at the RF front end. Moreover, ViPer NL-COMM enables supporting more information streams than available AP antennas when the streams are of low-rate, paving the way for enhanced massive-connectivity scenarios in next-generation wireless networks.

We report a systematic measurement of elliptic flow ($v_{2}$) of $K_{s}^{0}$, $Λ$, $\overlineΛ$, $ϕ$, $Ξ^{-}$, $\overlineΞ^{+}$, and $Ω^{-}$+$\overlineΩ^{+}$ at mid-rapidity ($|y| < 1.0$) for isobar, $^{96}_{44}$Ru+$^{96}_{44}$Ru and $^{96}_{40}$Zr+$^{96}_{40}$Zr, collisions at $\sqrt{s_{\mathrm {NN}}}$ = 200 GeV. The transverse momentum ($p_\mathrm{T}$) dependence of $v_{2}$ is studied for various centrality classes. The number of constituent quark scaling of (multi-)strange hadrons is found to hold approximately within 20%, suggesting the development of partonic collectivity in isobar collisions similar to that observed in Au+Au collisions at $\sqrt{s_{\mathrm {NN}}}$ = 200 GeV. The average $v_{2}$ ratio shows $\sim$2% deviation from unity in central and mid-central collisions for strange hadrons, indicating a difference in nuclear structure and deformation between the isobars. The $v_{2}$ in isobaric collisions is compared to Cu+Cu, Au+Au, and U+U collisions at similar collision energies. We observe an increase in $v_{2}(p_\mathrm{T})$ with increasing system size. The difference in $v_{2}$ between the isobar and other collision systems increases with $p_\mathrm{T}$. The results are compared with a multi-phase transport model calculations with a deformed density profile to provide further insight into the nuclear structure of these isobars.

Quantum sensors based on nitrogen vacancy (NV) centers in diamond have been a central topic in the sensing community for more than a decade. The extraordinary properties at room temperature of the spin system in diamond have made it one of the most prominent quantum platforms for the development of commercial quantum sensors. In particular, the sensitivity of the electronic spin in NV centers has made diamond-based magnetic sensors of special interest for their potential application in medical, industrial or navigation solutions. However, the use of these sensors for universal vector magnetometry was constrained by the need for previous knowledge on the field being measured to fully exploit their benefits. In this work, we show a method to perform unconditional vector magnetometry without the need of external information on the magnetic field, based only on the spatial arrangement of the diamond and the microwave antenna combination. While previous NV-based vector magnetometry methods require partial knowledge of the magnetic field (e.g. a calibrated bias field), we exploit the possibilities of selecting particular directions of the spins in the diamond with elliptically polarized microwave fields. We prove that our method allows to estimate both magnitude and direction of external magnetic fields without further assumptions or constraints.

This work presents a feasibility study aimed at enhancing the reconstruction sensitivity for rare heavy-flavour hadrons in Pb-Pb collisions in the ALICE experiment, using the $Ξ_{c}^{+}$ baryon as a benchmark. The $Ξ_{c}^{+}$ baryon has a low rate of production and some complex decay topologies as for instance the decay $Ξ_{c}^{+} \rightarrow Ξ^{-} + π^{+} + π^{+}$ considered in this work. Traditional simulation workflows involving event embedding and full detector response are computationally expensive and statistically limited, especially for rare signals. This study represents the first exploration of generative models within the heavy-flavour programme of ALICE. It uses a dataset of reconstructed physics quantities, such as momenta, positions, and decay vertex coordinates of $Ξ_{c}^{+}$ decay products in Pb-Pb collisions as input features, derived from augmented ALICE Monte Carlo simulations. Such features will serve as a training set for Generative Adversarial Networks (GANs) designed to generate statistically significant synthetic signal samples without the need for additional full simulations. While $Ξ_{c}^{+}$ serves as a benchmark, the broader objective is to enable searches for exotic heavy-flavour hadrons or other exotic states with complex decay patterns. By leveraging GAN-based augmentation, this approach supports rare-signal extraction in computationally demanding analyses and opens the way to broader applications of generative models in the ALICE heavy-flavour programme.

A compact, modular environmental control and solvothermal vapor annealing chamber designed for maintaining a controlled atmosphere with regard to solvent humidity and temperature is presented. The setup allows ex situ and in situ grazing incidence small-angle X-ray scattering (GISAXS) investigations of thin film self-assembly and reorganization. Its modular slotting system enables stable reconfiguration, including the integration of an adjustable magnetic field module. The temperature is maintained via a water-based heating and cooling loop supplemented by resistive elements, and the solvent vapor environment is regulated using a commercial controlled mixing and evaporation unit. The performance of the setup is validated through measurements of fill and quench times together with magnetic field mapping with Gauss meter measurements and finite element simulations. Further, the versatility of the setup is demonstrated with four research examples using the chamber for solvothermal vapor annealing of block copolymer thin films together with lab-based ex situ and in situ GISAXS measurements. The portable new design offers robust environmental control and flexibility for advanced thin film investigations both in the lab and at large scale facilities. The design can be adapted for grazing incidence small-angle neutron scattering, GISANS.

Behavioural distances generally offer more fine-grained means of comparing quantitative systems than two-valued behavioural equivalences. They often relate to quantitative modalities, which generate quantitative modal logics that characterize a given behavioural distance in terms of the induced logical distance. We develop a unified framework for behavioural distances and logics induced by a special type of modalities that lift two-valued predicates to quantitative predicates. A typical example is the probability operator, which maps a two-valued predicate $A$ to a quantitative predicate on probability distributions assigning to each distribution the respective probability of $A$. Correspondingly, the prototypical example of our framework is $ε$-bisimulation distance of Markov chains, which has recently been shown to coincide with the behavioural distance induced by the popular Lévy-Prokhorov distance on distributions. Other examples include behavioural distance on metric transition systems and Hausdorff behavioural distance on fuzzy transition systems. Our main generic results concern the polynomial-time extraction of distinguishing formulae in two characteristic modal logics: A two-valued logic with a notion of satisfaction up to $ε$, and a quantitative modal logic. These results instantiate to new results in many of the mentioned examples. Notably, we obtain polynomial-time extraction of distinguishing formulae for $ε$-bisimulation distance of Markov chains in a quantitative logic featuring a `generally' modality used in probabilistic knowledge representation.

Modern container-based microservices evolve through rapid deployment cycles, but CI/CD pipelines still rarely measure energy consumption, even though prior work shows that design patterns, code smells and refactorings affect energy efficiency. We present PPTAM$η$, an automated pipeline that integrates power and energy measurement into GitLab CI for containerised API systems, coordinating load generation, container monitoring and hardware power probes to collect comparable metrics at each commit. The pipeline makes energy visible to developers, supports version comparison for test engineers and enables trend analysis for researchers. We evaluate PPTAM$η$ on a JWT-authenticated API across four commits, collecting performance and energy metrics and summarising the architecture, measurement methodology and validation.

Performance antipatterns are known to degrade the responsiveness of microservice-based systems, but their impact on energy consumption remains largely unexplored. This paper empirically investigates whether widely studied performance antipatterns defined by Smith and Williams also negatively influence power usage. We implement ten antipatterns as isolated microservices and evaluate them under controlled load conditions, collecting synchronized measurements of performance, CPU and DRAM power consumption, and resource utilization across 30 repeated runs per antipattern. The results show that while all antipatterns degrade performance as expected, only a subset exhibit a statistically significant relationship between response time and increased power consumption. Specifically, several antipatterns reach CPU saturation, capping power draw regardless of rising response time, whereas others (\eg Unnecessary Processing, The Ramp) demonstrate energy-performance coupling indicative of inefficiency. Our results show that, while all injected performance antipatterns increase response time as expected, only a subset also behaves as clear energy antipatterns, with several cases reaching a nearly constant CPU power level where additional slowdowns mainly translate into longer execution time rather than higher instantaneous power consumption. The study provides a systematic foundation for identifying performance antipatterns that also behave as energy antipatterns and offers actionable insights for designing more energy-efficient microservices architectures.

The derived category of coherent systems is an interesting triangulated category associated with a smooth, projective curve $C$. These categories admit Bridgeland stability conditions, as recently shown by Feyzbakhsh and Novik. Their construction depends explicitly on the higher rank Brill-Noether theory of $C$. In this short note, we study the Feyzbakhsh--Novik stability conditions for a general curve of genus four. We show that these stability conditions degenerate to a stability condition on the Kuznetsov component of the corresponding nodal cubic threefold, using a result of Alexeev-Kuznetsov.

The Poisson equation governing a planet's gravitational field is posed on the unbounded domain, $\mathbb{R}^3$, whereas finite-element computations require bounded meshes. We implement and compare three strategies for handling the infinite exterior in the finite-element method: (i) naive domain truncation; (ii) Dirichlet-to-Neumann (DtN) map on a truncated boundary; (iii) multipole expansion on a truncated boundary. While all these methods are known within the geophysical literature, we discuss their parallel implementations within modern open-source finite-element codes, focusing specifically on the widely-used MFEM package. We consider both calculating the gravitational potential for a static density structure and computing the linearised perturbation to the potential caused by a displacement field - a necessary step for coupling self-gravitation into planetary dynamics. In contrast to some earlier studies, we find that the domain truncation method can provide accurate solutions at an acceptable cost, with suitable coarsening of the mesh within the exterior domain. Nevertheless, the DtN and multipole methods provide superior accuracy at a lower cost within large-scale parallel geophysical simulations despite their need for non-local communication associated with spherical harmonic expansions. The DtN method, in particular, admits an efficient parallel implementation based on an MPI-communicator limited to processors that contain part of the mesh's outer boundary. A series of further illustrative calculations are provided to show the potential of the DtN and multipole methods within realistic geophysical modelling.

We consider hypoelliptic symbols over a very regular Lie group and discuss monodromy for a spectral stratification using results of Nilsson and Bäcklund.

Traditional forest inventory systems, originally designed to quantify merchantable timber volume, often lack the spatial resolution and structural detail required for modern multi-resource ecosystem management. In this manuscript, we present an Enhanced Forest Inventory (EFI) and demonstrate its utility for high-resolution wildlife habitat mapping. The project area covers 270,000 acres of the Eldorado National Forest in California's Sierra Nevada. By integrating 118 ground-truth Forest Inventory and Analysis (FIA) plots with multi-modal remote sensing data (LiDAR, aerial photography, and Sentinel-2 satellite imagery), we developed predictive models for key forest attributes. Our methodology employed a two-tier segmentation approach, partitioning the landscape into approximately 575,000 reporting units with an average size of 0.5 acre to capture forest heterogeneity. We utilized an Elastic-Net Regression framework and automated feature selection to relate remote sensing metrics to ground-measured variables such as basal area, stems per acre, and canopy cover. These physical metrics were translated into functional habitat attributes to evaluate suitability for two focal species: the California Spotted Owl (Strix occidentalis occidentalis) and the Pacific Fisher (Pekania pennanti). Our analysis identified 25,630 acres of nesting and 26,622 acres of foraging habitat for the owl, and 25,636 acres of likely habitat for the fisher based on structural requirements like large-diameter trees and high canopy closure. The results demonstrate that EFIs provide a critical bridge between forestry and conservation ecology, offering forest managers a spatially explicit tool to monitor ecosystem health and manage vulnerable species in complex environments.

In the Contention Resolution problem $n$ parties each wish to have exclusive use of a shared resource for one unit of time. The problem has been studied since the early 1970s, under a variety of assumptions on feedback given to the parties, how the parties wake up, knowledge of $n$, and so on. The most consistent assumption is that parties do not have access to a global clock, only their local time since wake-up. This is surprising because the assumption of a global clock is both technologically realistic and algorithmically interesting. It enriches the problem, and opens the door to entirely new techniques. Our primary results are: [1] We design a new Contention Resolution protocol that guarantees latency $$O\left(\left(n\log\log n\log^{(3)} n\log^{(4)} n\cdots \log^{(\log^* n)} n\right)\cdot 2^{\log^* n}\right) \le n(\log\log n)^{1+o(1)}$$ in expectation and with high probability. This already establishes at least a roughly $\log n$ complexity gap between randomized protocols in GlobalClock and LocalClock. [2] Prior analyses of randomized ContentionResolution protocols in LocalClock guaranteed a certain latency with high probability, i.e., with probability $1-1/\text{poly}(n)$. We observe that it is just as natural to measure expected latency, and prove a $\log n$-factor complexity gap between the two objectives for memoryless protocols. The In-Expectation complexity is $Θ(n \log n/\log\log n)$ whereas the With-High-Probability latency is $Θ(n\log^2 n/\log\log n)$. Three of these four upper and lower bounds are new. [3] Given the complexity separation above, one would naturally want a ContentionResolution protocol that is optimal under both the In-Expectation and With-High-Probability metrics. This is impossible! It is even impossible to achieve In-Expectation latency $o(n\log^2 n/(\log\log n)^2)$ and With-High-Probability latency $n\log^{O(1)} n$ simultaneously.